Temporal Dynamics Modeling
Temporal Dynamics Modeling is a computational framework within sequential and session-based recommendation that explicitly captures and represents the time-varying patterns and evolution of user-item interactions over time to improve predictive accuracy.
143
Publications
9.7K
Citations
470
Authors
182
Institutions
Publications per year
2017–2026
88
143
Collaborative filtering with temporal dynamics
Yehuda Koren · 2009 · 1.2K citations
Collaborative filtering with temporal dynamics
Yehuda Koren · Communications of the ACM · 2010 · 776 citations
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
2019 · 625 citations · Full text
Time Interval Aware Self-Attention for Sequential Recommendation
Jiacheng Li, Yujie Wang, Julian McAuley · 2020 · 613 citations · Full text
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182
Stanford University
Stanford, United States
6 h-index
10 publications
1.6K citations
Tsinghua University
Beijing, China
6 h-index
22 publications
816 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
10 publications
280 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
10 publications
1K citations

Peking University
Beijing, China
4 h-index
12 publications
404 citations

East China Normal University
Shanghai, China
4 h-index
10 publications
256 citations
University of Fribourg
Fribourg, Switzerland
4 h-index
14 publications
208 citations
Microsoft (United States)
Redmond, United States
4 h-index
13 publications
967 citations
1–8 of 182
Repository · 10 publications · 215 citations
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Conference · 6 publications · 1.2K citations
6
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4 publications · 239 citations
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3 publications · 50 citations
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3 publications · 42 citations
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